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Applications and methods of state of the art microsimulation modelling.
Selected and revised papers from the conference on "Microsimulation in government policy and forecasting" held in Portland, Maine in July 1997; the volume also contains invited contributions by experts in the field, and a separate part on practical microsimulation models--Preface.
This book is a practical guide on how to design, create and validate a spatial microsimulation model. These models are becoming more popular as academics and policy makers recognise the value of place in research and policy making. Recent spatial microsimulation models have been used to analyse health and social disadvantage for small areas; and to look at the effect of policy change for small areas. This provides a powerful analysis tool for researchers and policy makers. This book covers preparing the data for spatial microsimulation; a number of methods for both static and dynamic spatial microsimulation models; validation of the models to ensure the outputs are reasonable; and the future of spatial microsimulation. The book will be an essential handbook for any researcher or policy maker looking to design and create a spatial microsimulation model. This book will also be useful to those policy makers who are commissioning a spatial microsimulation model, or looking to commission work using a spatial microsimulation model, as it provides information on the different methods in a non-technical way.
Los desarrollos en el ámbito de la investigación sobre la evaluación de políticas públicas están experimentando actualmente un gran avance. En este contexto, las técnicas de microsimulación -basadas en la representación del comportamiento de los individuos frente a cambios reales o hipotéticos en su entorno económico e institucional- han adquirido particular relevancia por su capacidad para evaluar a priori diferentes escenarios y facilitar la toma de decisiones. Las técnicas de simulación se realizan con modelos de absoluta precisión y exactitud que permiten estudiar y predecir el impacto y los efectos de una política sobre una muestra de individuos, familias o empresas representativa de la población total. Este libro presenta la microsimulación como técnica de evaluación de las políticas públicas, al mismo tiempo que propone una revisión razonada de los recientes avances. Una conclusión común es que, gracias a un modelo de microsimulación, es posible identificar la mejor política de redistribución posible (en el sentido de maximizar una determinada función de bienestar social). De manera general, mediante el uso de esta técnica es posible hacer complementarios los enfoques macro de equilibrio económico general y micro de simulación de los comportamientos individuales. La presente publicación ofrece una herramienta de referencia a investigadores, académicos, políticos y analistas.
The strengths and abilities children develop from infancy through adolescence are crucial for their physical, emotional, and cognitive growth, which in turn help them to achieve success in school and to become responsible, economically self-sufficient, and healthy adults. Capable, responsible, and healthy adults are clearly the foundation of a well-functioning and prosperous society, yet America's future is not as secure as it could be because millions of American children live in families with incomes below the poverty line. A wealth of evidence suggests that a lack of adequate economic resources for families with children compromises these children's ability to grow and achieve adult success, hurting them and the broader society. A Roadmap to Reducing Child Poverty reviews the research on linkages between child poverty and child well-being, and analyzes the poverty-reducing effects of major assistance programs directed at children and families. This report also provides policy and program recommendations for reducing the number of children living in poverty in the United States by half within 10 years.
Microsimulation Modelling involves the application of simulation methods to micro data for the purposes of evaluating the effectiveness and improving the design of public policy. The field has been applied to many different policies within both government and academia. This handbook describes and discusses the main issues within the field.
Approaches to energy use modeling; Residential energy demand simulation models; Residential energy policy analysis: the alternative policy scenarios; Simulation results from the REEPS model; Simulation results from the ORNL model; A comparative analysis of model performance: REEPS versus ORLN.
Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling. Dr Azizur Rahman is a Senior Lecturer in Statistics and convenor of the Graduate Program in Applied Statistics at the Charles Sturt University, and an Adjunct Associate Professor of Public Health and Biostatistics at the University of Canberra. His research encompasses small area estimation, applied economics, microsimulation modeling, Bayesian inference and public health. He has more than 60 scholarly publications including two books. Dr. Rahman’s research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM). Professor Ann Harding, AO is an Emeritus Professor of Applied Economics and Social Policy at the National Centre for Social and Economic Modelling (NATSEM) of the University of Canberra. She was the founder and inaugural Director of this world class Research Centre for more than sixteen years, and also a co-founder of the International Microsimulation Association (IMA) and served as the inaugural elected president of IMA from 2004 to 2011. She is a fellow of the Academy of the Social Sciences in Australia. She has more than 300 publications including several books in microsimulation modeling.
Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Spatial Microsimulation with R is the first practical book to illustrate this approach in a modern statistical programming language. Get Insight into Complex Behaviors The book progresses from the principles underlying population synthesis toward more complex issues such as household allocation and using the results of spatial microsimulation for agent-based modeling. This equips you with the skills needed to apply the techniques to real-world situations. The book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets using the recent R packages ipfp and mipfp. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility. Implement the Methods on Your Own Data Full of reproducible examples using code and data, the book is suitable for students and applied researchers in health, economics, transport, geography, and other fields that require individual-level data allocated to small geographic zones. By explaining how to use tools for modeling phenomena that vary over space, the book enhances your knowledge of complex systems and empowers you to provide evidence-based policy guidance.